Introduction
Dengue is the most important arboviral infection of humans. In endemic countries the
scale of the dengue disease burden imparts an economic cost [1] and strains fragile
health care systems. There are no licensed vaccines for prevention of dengue, and
the public health response in endemic countries relies mostly on combating the principal
mosquito vector, Aedes aegypti, via insecticides and breeding site removal. The sustained
transmission of dengue in endemic settings together with its increasing global footprint
indicates existing disease control strategies have been unsuccessful [2].
Novel vector control approaches to limit dengue virus (DENV) transmission include
release of Ae. aegypti that carry transgenes that result in highly penetrant, dominant,
late-acting, female-specific lethality [3]. In field cage experiments, the release
of such mosquitoes in sufficient numbers results in eradication of the mosquito population
[4]. Another strategy involves embryonic introduction of the obligate intracellular
insect bacterium, Wolbachia, into strains of Ae. aegypti
[5]. Strikingly, Wolbachia-infected Ae. aegypti are partially resistant to infection
with DENV [6], and by virtue of the intrinsic capacity of some strains of Wolbachia
to invade insect populations [6], [7], there is the prospect of achieving widespread
biological resistance to DENV amongst Ae. aegypti populations. The life-shortening
impact of some Wolbachia strains could also contribute to reductions in disease transmission
[5]. The first entomological field trials of mosquitoes infected with Wolbachia (wMel
and wMelPop strains) have now been successfully carried out in Cairns, Australia and
have demonstrated that Wolbachia can establish itself at very high prevalence in field
populations of Ae. aegypti
[7]. However, the prospects of demonstrating reduction in DENV transmission in Cairns
are slim given the episodic, imported nature of dengue outbreaks in this region.
A critical challenge for all entomological approaches to control of vector-borne disease
is how best to demonstrate efficacy in reducing disease transmission [8]. In principal,
the high force of infection in dengue endemic countries should assist an evidence-gathering
approach to this challenge. However, a feature of dengue epidemiology is that it is
spatially and temporally heterogeneous [9]–[11]. Thus oscillations in disease incidence
over time are common for a given region of transmission, and within each region it
is common for focal “hot spots” of transmission to exist [3]. This heterogeneity in
transmission means that uncontrolled observational studies of dengue transmission
in a community where, for example, Wolbachia-infected Ae. aegypti have been released
could take many years or decades to yield evidence that is suggestive of a benefit.
Equally, the heterogeneity of dengue transmission poses challenges to traditional
clinical trial approaches, as does the non-stationary nature of mosquito populations
[8]. Here we review design and statistical considerations relevant to the conduct
of clinical trials of these novel interventions and the practical challenges posed
by the epidemiology of dengue in endemic settings. Whilst our discussion of trial
design is focused on Wolbachia-infected Ae. aegypti, it is also relevant to other
vector control interventions, such as genetically engineered male mosquitoes carrying
a dominant lethal gene [4], insecticide-impregnated nets [12], or larvacides [13].
Methods
Cluster randomised trials (CRTs) are the gold standard design to provide evidence
on the efficacy of an intervention that has community-wide impact [14]. Cluster formation
is a crucial aspect of the design of a CRT and requires prior mapping of the study
area with respect to dengue sero-prevalence, demographics, and information on movement
of individuals. Experience from the Cairns (Australia) release shows that it is feasible
to achieve a prevalence of Wolbachia infection in A. aegypti mosquitoes of nearly
100% in treatment clusters within 6 months after first release [7]. Clusters need
to be sufficiently geographically separated to ensure that A. aegypti mosquitoes present
in control clusters remain virtually free of Wolbachia for the entire study period.
We consider the incidence of DENV-seroconversions during a trial as a suitable primary
endpoint and DENV-naïve children aged 2–5 years living in each cluster as an optimal
“sentinel” cohort for serological surveillance. Young children are less likely to
spend substantial periods of time outside of their residence and local community (and
hence outside of the “treatment umbrella”) than more mobile older children and adults.
In addition, DENV-prevalence in older children is higher and those remaining naïve
and hence eligible for the study are potentially less representative of the full population
(for example, for socio-economic reasons).
Two alternative designs are considered. The first is the classical parallel two-armed
cluster randomised trial (PCRT) in which each recruited cluster is randomised to intervention
or control, and the intervention is implemented simultaneously across the relevant
clusters. Thus the control clusters provide contemporaneous controls for the intervention
clusters. The other design considered is a stepped wedge cluster randomised trial
(SWCRT) in which each cluster is assigned to the control treatment initially and clusters
are subsequently crossed-over to the intervention in a random selection at fixed time
points until eventually all clusters are under treatment [15], [16]. As dengue is
a seasonal disease, selected cross-over time points should reflect this. As an example,
for a 3-year study period, the SWCRT has: all clusters as controls for year 1; half
of the clusters as controls and half as intervention, randomly selected, for year
2; and all clusters on intervention in year 3. Diagrams of both designs are provided
in Text S1.
SWCRTs have been most frequently used for evaluating interventions during routine
implementation such as the evaluation of a vaccine on the community level following
a successful individual randomised trial. From a logistic perspective, they are attractive,
because the intervention can be rolled out in a step-wise fashion and evaluated. As
clusters are their own controls, SWCRTs are less sensitive to between-cluster variation
and thus might require a lower sample size compared to parallel designs [15]. However,
strong temporal effects may greatly reduce the precision of estimates as all clusters
start out in the control arm and end as intervention clusters. Secular trends of dengue
during the study period could confound the treatment effect causing bias. SWCRTs are
less flexible for trial adaptations such as an extension of the follow-up period if
the observed DENV-incidence is lower than expected, as all clusters have already crossed-over
to the intervention at this time point.
Cluster size and cluster separation are important considerations in the design of
all CRTs, but they require particular attention in trials of vector control interventions,
for which entomological and community considerations need be taken into account. Entomological
considerations include the dispersal of Wolbachia-infected mosquitoes to ensure a
persistent and homogenous effect in treatment clusters without undue contamination
into untreated clusters that serve as controls. For dengue trials community considerations
include the extent of daily movement within and between clusters that the surveillance
cohorts are likely to undertake; if the clusters are too small this movement may be
excessive, and cause further reduction in any treatment effect. Thus, data on movement
patterns of children eligible to join the surveillance cohort together with more information
on the limits of spatial dispersal of Wolbachia-infected mosquitoes are essential
before the cluster formation stage of any trial. An approach that is widely adopted
in CRTs is the so-called “fried-egg” design [14], in which the whole cluster receives
the allocated treatment but only the inner area of the cluster (the “egg-yolk”) is
used for surveillance since the treatment effect in this inner area is less affected
by spill-over from neighbouring clusters that may be in the opposite treatment arm.
We would therefore suggest that the surveillance cohort in each cluster be drawn from
this inner area of each cluster.
Sample Size Requirements of a CRT
Sample size requirements for CRTs of a Wolbachia intervention (or other community-based
intervention) depend critically on the size of the intervention effect and on both
the magnitude and the variability (temporal and spatial) of seroconversion rates between
clusters. To assess this variability in an example, we used published data from 12
primary schools in Kamphaeng Phet, Thailand, followed over a 3-year period [10] where
the overall yearly DENV infection incidences were 7.9%, 6.5%, and 2.2%.
A mixed-effects Poisson-regression model fitted to these data gave coefficients of
variation (cv, i.e., SD/mean) for yearly DENV infection incidence of 0.27 for between-school
variation, 0.57 for annual variation, and 0.85 for residual variation (i.e., variation
that cannot be explained by systematic spatial or temporal variation, respectively,
and corresponds to localized school and year specific variation). A detailed description
of the model used to derive these coefficients of variation can be found in Text S1.
The overall between-school coefficient of variation over the 3-year period was 0.52.
The same model fit to data from 43 villages in Cambodia [9], also showed that temporal
and residual variation are more pronounced than spatial variation (unpublished data).
We then used the incidence and variability data reported above to simulate hypothetical
PCRT and SWCRT trials. Additional assumptions for the trial simulations were a study
duration of 3 years and a surveillance cohort of 100 children in each cluster. We
varied the intervention effect between a 40% and an 80% decrease of DENV seroconversion
in intervention clusters compared to controls. Allowing for the fact that some children
in intervention clusters will experience infections outside of the intervention area,
we regard an effect of a 50%–60% reduction as realistic in our target population.
Details regarding the set-up of the simulation study and the statistical analysis
of simulated trials are provided in Text S1.
Results
Sample size requirements for the two designs and for varying treatment effects are
shown in Figure 1 and requirements for several alternative scenarios are given in
Text S1. The required total sample sizes to detect a 60% or 50% reduction of dengue
in the intervention arm with 80% power were 20 or 32 clusters, respectively, for a
PCRT compared to 40 or 72 clusters for a SWCRT. The SWCRT design generally required
substantially higher sample sizes except in the unrealistic situation of spatial but
no temporal or residual variation.
10.1371/journal.pntd.0001937.g001
Figure 1
Sample size estimates for a PCRT or a SWCRT.
Total number of clusters required for a PCRT (black lines) or a SWCRT (blue lines)
depending on the size of the intervention effect. Solid lines correspond to 90% power,
dashed lines to 80% power. Simulations are based on parameters determined from the
Kamphaeng Phet dengue cohort (Thailand) (described in [10]) with three time periods
each of 1-year duration, a surveillance cohort of 100 children in each cluster, and
a two-sided significance level of 5%.
Conclusions
A parallel cluster-randomised trial is the design of choice for testing novel entomological
methods of dengue control. Under realistic assumptions we show it to require a substantially
lower sample size than a stepped wedge design. Sample size requirements for a parallel
design are relatively modest; our example gave a minimum sample size of 20 clusters
(ten per study arm) with each cluster providing 100 person-years of follow-up per
year and a follow-up duration of 3 years. Although careful planning and substantial
funding are required to run such a trial, the benefits of having a robust evidence-base
from which to promote programmatic roll-out and/or further optimisation of the strategy
should prove invaluable.
Supporting Information
Text S1
Statistical appendix containing: (1) a diagram of a parallel two-arm cluster randomised
trial (PCRT) and a stepped wedge cluster randomised trial (SWCRT), (2) details regarding
the determination of coefficients of variation for the Thailand data, and (3) details
regarding the simulation study to compare PCRT versus SWCRT designs.
(DOCX)
Click here for additional data file.